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Disturbance observer-based sliding mode control for consensus tracking of chaotic nonlinear multi-agent systems

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  • Derakhshannia, Mehran
  • Moosapour, Seyyed Sajjad

Abstract

This paper deals with the finite-time consensus of chaotic MIMO nonlinear heterogeneous multi-agent systems subjected to matched uncertainties and disturbances. This study proposes a consensus protocol utilizing a novel dynamic sliding mode control, ensuring robust performance and chattering attenuation. For this purpose, firstly, a new time-varying nonlinear sliding manifold is introduced that guarantees exponential finite-time stability. Secondly, a novel reaching law is established that ensures fixed reaching time independent of initial conditions. The fixed reaching time enables the specification of the reaching time by considering the problem constraints. Then, a novel terminal disturbance observer is proposed to efficiently estimate the overall effect of uncertainties and disturbances in the finite-time. Finally, an adaptive form of the proposed controller is presented by incorporating the disturbance observer into the proposed sliding mode control. The proposed consensus protocols are applied to a multi-agent system consisting of two well-known chaotic power systems (PMSM and BLDCM). Computer simulations and comparative studies confirm the results of this study in terms of tracking errors and fast convergence.

Suggested Citation

  • Derakhshannia, Mehran & Moosapour, Seyyed Sajjad, 2022. "Disturbance observer-based sliding mode control for consensus tracking of chaotic nonlinear multi-agent systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 194(C), pages 610-628.
    • Handle: RePEc:eee:matcom:v:194:y:2022:i:c:p:610-628
    DOI: 10.1016/j.matcom.2021.12.017
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    References listed on IDEAS

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    1. Yaghoubi, Zahra, 2020. "Robust cluster consensus of general fractional-order nonlinear multi agent systems via adaptive sliding mode controller," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 172(C), pages 15-32.
    2. Lavanya, S. & Nagarani, S., 2022. "Leader-following consensus of multi-agent systems with sampled-data control and looped functionals," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 191(C), pages 120-133.
    3. Yacine, Zedjiga & Hamiche, Hamid & Djennoune, Saïd & Mammar, Saïd, 2022. "Finite-time impulsive observers for nonlinear systems represented by Takagi–Sugeno models: Application to a chaotic system," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 192(C), pages 321-352.
    4. Yang Fei & Peng Shi & Cheng-Chew Lim, 2020. "Neural network adaptive dynamic sliding mode formation control of multi-agent systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 51(11), pages 2025-2040, July.
    5. Wang, Cong & Zhang, Hongli & Fan, Wenhui & Ma, Ping, 2018. "Adaptive control method for chaotic power systems based on finite-time stability theory and passivity-based control approach," Chaos, Solitons & Fractals, Elsevier, vol. 112(C), pages 159-167.
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    Cited by:

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    2. Otkel, Madina & Ganesan, Soundararajan & Rajan, Rakkiyappan & Kashkynbayev, Ardak, 2024. "Finite-time/fixed-time synchronization of memristive shunting inhibitory cellular neural networks via sliding mode control," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 222(C), pages 252-263.

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